On the convergence of the iterative solution of the likelihood equations
نویسنده
چکیده
To determine the maximum likelihood estimate in case of the iterative solution of the likelihood equations we need a convergence criterion. Usually numerically motivated convergence criteria are used; we propose a statistically motivated convergence criterion. Our criterion reduces the number of iterations tremendously. The iterative algorithm to solve the equations is known to be unstable in the neighborhood of the exact solution. Our method avoids this numerical unstable region. The theory is validated by simulations.
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